Example:

Output: Generates a new isNewYork column, in which each row contains the value New York, New York! when the corresponding value in the State column is NY. Otherwise, the value in isNewYork is some other place.

Nested IF Example: 

You can build IF statements within IF statements as in the following example, in which the second IF is evaluated if the first one evaluates to false:

A more detailed nested example is available below.

In the following, if the test expression evaluates to true, the true_expression is executed. Otherwise, the false_expression is executed.

IF(test_expression, true_expression,false_expression)

All of these expressions can be constants (strings, integers, or any other supported literal value) or sophisticated elements of logic, although the test expression must evaluate to a Boolean value.

test_expression

This parameter contains the expression to evaluate. This expression must resolve to a Boolean (true or false) value.

true_expression, false_expression

The true_expression determines the value or conditional that is generated if the test_expression evaluates to true. If the test is false, then the false_expression applies.

These expressions typically generate output values and can use a combination of literals, functions, and column references.

• A true expression is required. You can insert a blank expression ( "").
• If a false expression is not provided, false results yield a value of false.

Example - Basic Usage

Example data:

Transforms:

Results:

Your output looks like the following:

Example - Stock Quotes

This example demonstrates how you can chain together multiple if/then/else conditions within a single transform step.

You have a set of stock prices that you want to analyze. Based on a set of rules, you want to determine any buy, sell, or hold action to take. 

Source:

Transform:

You can perform evaluations of this data using the IF function to determine if you want to take action.

To assist in evaluation, you might first want to create columns that contain the cost (Basis) and the current value (CurrentValue) for each stock:

Now, you can build some rules based on the spread between Basis and CurrentValue.

Single IF version: In this case, the most important action is determining if it is time to sell. The following rule writes a sell notification if the current value is $1000 or more than the cost. Otherwise, no value is written to the action column.

Nested IF version: But what about buying more? The following transform is an edit to the previous one. In this new version, the sell test is performed, and if false, writes a buy action if the CurrentPrice is within 10% of the BuyPrice. 

This second evaluation is performed after the first one, as it replaces the else clause, which did nothing in the previous version. In the Recipe Panel, click the previous transform and edit it, replacing it with the new version:

If neither test evaluates to true, the written action is hold. 

You might want to format some of your columns using dollar formatting, as in the following:

Results:

After moving your columns, your dataset should look like the following, if you completed the number formatting steps: